<!DOCTYPE html>
<html lang="en-us">
  <head>

    <meta http-equiv="content-type" content="text/html; charset=utf-8">
    
<meta charset="UTF-8">
<title>Find file structure API | Elasticsearch Guide [7.7] | Elastic</title>
<link rel="home" href="index.html" title="Elasticsearch Guide [7.7]">
<link rel="up" href="ml-apis.html" title="Machine learning anomaly detection APIs">
<link rel="prev" href="ml-estimate-model-memory.html" title="Estimate anomaly detection jobs model memory API">
<link rel="next" href="ml-flush-job.html" title="Flush jobs API">
<meta name="DC.type" content="Learn/Docs/Elasticsearch/Reference/7.7">
<meta name="DC.subject" content="Elasticsearch">
<meta name="DC.identifier" content="7.7">
<meta name="robots" content="noindex,nofollow">
    <meta http-equiv="X-UA-Compatible" content="IE=edge">
    <meta name="viewport" content="width=device-width, initial-scale=1">
    <script src="https://cdn.optimizely.com/js/18132920325.js"></script>
    <link rel="apple-touch-icon" sizes="57x57" href="/apple-icon-57x57.png">
    <link rel="apple-touch-icon" sizes="60x60" href="/apple-icon-60x60.png">
    <link rel="apple-touch-icon" sizes="72x72" href="/apple-icon-72x72.png">
    <link rel="apple-touch-icon" sizes="76x76" href="/apple-icon-76x76.png">
    <link rel="apple-touch-icon" sizes="114x114" href="/apple-icon-114x114.png">
    <link rel="apple-touch-icon" sizes="120x120" href="/apple-icon-120x120.png">
    <link rel="apple-touch-icon" sizes="144x144" href="/apple-icon-144x144.png">
    <link rel="apple-touch-icon" sizes="152x152" href="/apple-icon-152x152.png">
    <link rel="apple-touch-icon" sizes="180x180" href="/apple-icon-180x180.png">
    <link rel="icon" type="image/png" href="/favicon-32x32.png" sizes="32x32">
    <link rel="icon" type="image/png" href="/android-chrome-192x192.png" sizes="192x192">
    <link rel="icon" type="image/png" href="/favicon-96x96.png" sizes="96x96">
    <link rel="icon" type="image/png" href="/favicon-16x16.png" sizes="16x16">
    <link rel="manifest" href="/manifest.json">
    <meta name="apple-mobile-web-app-title" content="Elastic">
    <meta name="application-name" content="Elastic">
    <meta name="msapplication-TileColor" content="#ffffff">
    <meta name="msapplication-TileImage" content="/mstile-144x144.png">
    <meta name="theme-color" content="#ffffff">
    <meta name="naver-site-verification" content="936882c1853b701b3cef3721758d80535413dbfd">
    <meta name="yandex-verification" content="d8a47e95d0972434">
    <meta name="localized" content="true">
    <meta name="st:robots" content="follow,index">
    <meta property="og:image" content="https://www.elastic.co/static/images/elastic-logo-200.png">
    <link rel="shortcut icon" href="/favicon.ico" type="image/x-icon">
    <link rel="icon" href="/favicon.ico" type="image/x-icon">
    <link rel="apple-touch-icon-precomposed" sizes="64x64" href="/favicon_64x64_16bit.png">
    <link rel="apple-touch-icon-precomposed" sizes="32x32" href="/favicon_32x32.png">
    <link rel="apple-touch-icon-precomposed" sizes="16x16" href="/favicon_16x16.png">
    <!-- Give IE8 a fighting chance -->
    <!--[if lt IE 9]>
    <script src="https://oss.maxcdn.com/html5shiv/3.7.2/html5shiv.min.js"></script>
    <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
    <![endif]-->
    <link rel="stylesheet" type="text/css" href="/guide/static/styles.css">
  </head>

  <!--© 2015-2021 Elasticsearch B.V. Copying, publishing and/or distributing without written permission is strictly prohibited.-->

  <body>
    <!-- Google Tag Manager -->
    <script>dataLayer = [];</script><noscript><iframe src="//www.googletagmanager.com/ns.html?id=GTM-58RLH5" height="0" width="0" style="display:none;visibility:hidden"></iframe></noscript>
    <script>(function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start': new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0], j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src= '//www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f); })(window,document,'script','dataLayer','GTM-58RLH5');</script>
    <!-- End Google Tag Manager -->

    <!-- Global site tag (gtag.js) - Google Analytics -->
    <script async src="https://www.googletagmanager.com/gtag/js?id=UA-12395217-16"></script>
    <script>
      window.dataLayer = window.dataLayer || [];
      function gtag(){dataLayer.push(arguments);}
      gtag('js', new Date());
      gtag('config', 'UA-12395217-16');
    </script>

    <!--BEGIN QUALTRICS WEBSITE FEEDBACK SNIPPET-->
    <script type="text/javascript">
      (function(){var g=function(e,h,f,g){
      this.get=function(a){for(var a=a+"=",c=document.cookie.split(";"),b=0,e=c.length;b<e;b++){for(var d=c[b];" "==d.charAt(0);)d=d.substring(1,d.length);if(0==d.indexOf(a))return d.substring(a.length,d.length)}return null};
      this.set=function(a,c){var b="",b=new Date;b.setTime(b.getTime()+6048E5);b="; expires="+b.toGMTString();document.cookie=a+"="+c+b+"; path=/; "};
      this.check=function(){var a=this.get(f);if(a)a=a.split(":");else if(100!=e)"v"==h&&(e=Math.random()>=e/100?0:100),a=[h,e,0],this.set(f,a.join(":"));else return!0;var c=a[1];if(100==c)return!0;switch(a[0]){case "v":return!1;case "r":return c=a[2]%Math.floor(100/c),a[2]++,this.set(f,a.join(":")),!c}return!0};
      this.go=function(){if(this.check()){var a=document.createElement("script");a.type="text/javascript";a.src=g;document.body&&document.body.appendChild(a)}};
      this.start=function(){var a=this;window.addEventListener?window.addEventListener("load",function(){a.go()},!1):window.attachEvent&&window.attachEvent("onload",function(){a.go()})}};
      try{(new g(100,"r","QSI_S_ZN_emkP0oSe9Qrn7kF","https://znemkp0ose9qrn7kf-elastic.siteintercept.qualtrics.com/WRSiteInterceptEngine/?Q_ZID=ZN_emkP0oSe9Qrn7kF")).start()}catch(i){}})();
    </script><div id="ZN_emkP0oSe9Qrn7kF"><!--DO NOT REMOVE-CONTENTS PLACED HERE--></div>
    <!--END WEBSITE FEEDBACK SNIPPET-->

    <div id="elastic-nav" style="display:none;"></div>
    <script src="https://www.elastic.co/elastic-nav.js"></script>

    <!-- Subnav -->
    <div>
      <div>
        <div class="tertiary-nav d-none d-md-block">
          <div class="container">
            <div class="p-t-b-15 d-flex justify-content-between nav-container">
              <div class="breadcrum-wrapper"><span><a href="/guide/" style="font-size: 14px; font-weight: 600; color: #000;">Docs</a></span></div>
            </div>
          </div>
        </div>
      </div>
    </div>

    <div class="main-container">
      <section id="content">
        <div class="content-wrapper">

          <section id="guide" lang="en">
            <div class="container">
              <div class="row">
                <div class="col-xs-12 col-sm-8 col-md-8 guide-section">
                  <!-- start body -->
                  <div class="page_header">
<strong>IMPORTANT</strong>: No additional bug fixes or documentation updates
will be released for this version. For the latest information, see the
<a href="../current/index.html">current release documentation</a>.
</div>
<div id="content">
<div class="breadcrumbs">
<span class="breadcrumb-link"><a href="index.html">Elasticsearch Guide [7.7]</a></span>
»
<span class="breadcrumb-link"><a href="rest-apis.html">REST APIs</a></span>
»
<span class="breadcrumb-link"><a href="ml-apis.html">Machine learning anomaly detection APIs</a></span>
»
<span class="breadcrumb-node">Find file structure API</span>
</div>
<div class="navheader">
<span class="prev">
<a href="ml-estimate-model-memory.html">« Estimate anomaly detection jobs model memory API</a>
</span>
<span class="next">
<a href="ml-flush-job.html">Flush jobs API »</a>
</span>
</div>
<div class="section xpack">
<div class="titlepage"><div><div>
<h2 class="title">
<a id="ml-find-file-structure"></a>Find file structure API<a class="edit_me edit_me_private" rel="nofollow" title="Editing on GitHub is available to Elastic" href="https://github.com/elastic/elasticsearch/edit/7.7/docs/reference/ml/anomaly-detection/apis/find-file-structure.asciidoc">edit</a><a class="xpack_tag" href="/subscriptions"></a>
</h2>
</div></div></div>

<div class="warning admon">
<div class="icon"></div>
<div class="admon_content">
<p>This functionality is experimental and may be changed or removed completely in a future release. Elastic will take a best effort approach to fix any issues, but experimental features are not subject to the support SLA of official GA features.</p>
</div>
</div>
<p>Finds the structure of a text file. The text file must contain data that is
suitable to be ingested into Elasticsearch.</p>
<div class="section">
<div class="titlepage"><div><div>
<h3 class="title">
<a id="ml-find-file-structure-request"></a>Request<a class="edit_me edit_me_private" rel="nofollow" title="Editing on GitHub is available to Elastic" href="https://github.com/elastic/elasticsearch/edit/7.7/docs/reference/ml/anomaly-detection/apis/find-file-structure.asciidoc">edit</a>
</h3>
</div></div></div>
<p><code class="literal">POST _ml/find_file_structure</code></p>
</div>

<div class="section">
<div class="titlepage"><div><div>
<h3 class="title">
<a id="ml-find-file-structure-prereqs"></a>Prerequisites<a class="edit_me edit_me_private" rel="nofollow" title="Editing on GitHub is available to Elastic" href="https://github.com/elastic/elasticsearch/edit/7.7/docs/reference/ml/anomaly-detection/apis/find-file-structure.asciidoc">edit</a>
</h3>
</div></div></div>
<div class="ulist itemizedlist">
<ul class="itemizedlist">
<li class="listitem">
If the Elasticsearch security features are enabled, you must have <code class="literal">monitor_ml</code> or
<code class="literal">monitor</code> cluster privileges to use this API. See
<a class="xref" href="security-privileges.html" title="Security privileges">Security privileges</a>.
</li>
</ul>
</div>
</div>

<div class="section">
<div class="titlepage"><div><div>
<h3 class="title">
<a id="ml-find-file-structure-desc"></a>Description<a class="edit_me edit_me_private" rel="nofollow" title="Editing on GitHub is available to Elastic" href="https://github.com/elastic/elasticsearch/edit/7.7/docs/reference/ml/anomaly-detection/apis/find-file-structure.asciidoc">edit</a>
</h3>
</div></div></div>
<p>This API provides a starting point for ingesting data into Elasticsearch in a format that
is suitable for subsequent use with other machine learning functionality.</p>
<p>Unlike other Elasticsearch endpoints, the data that is posted to this endpoint does not
need to be UTF-8 encoded and in JSON format. It must, however, be text; binary
file formats are not currently supported.</p>
<p>The response from the API contains:</p>
<div class="ulist itemizedlist">
<ul class="itemizedlist">
<li class="listitem">
A couple of messages from the beginning of the file.
</li>
<li class="listitem">
Statistics that reveal the most common values for all fields detected within
the file and basic numeric statistics for numeric fields.
</li>
<li class="listitem">
Information about the structure of the file, which is useful when you write
ingest configurations to index the file contents.
</li>
<li class="listitem">
Appropriate mappings for an Elasticsearch index, which you could use to ingest the file
contents.
</li>
</ul>
</div>
<p>All this information can be calculated by the structure finder with no guidance.
However, you can optionally override some of the decisions about the file
structure by specifying one or more query parameters.</p>
<p>Details of the output can be seen in the
<a class="xref" href="ml-find-file-structure.html#ml-find-file-structure-examples" title="Examples">examples</a>.</p>
<p>If the structure finder produces unexpected results for a particular file,
specify the <code class="literal">explain</code> query parameter. It causes an <code class="literal">explanation</code> to appear in
the response, which should help in determining why the returned structure was
chosen.</p>
</div>

<div class="section">
<div class="titlepage"><div><div>
<h3 class="title">
<a id="ml-find-file-structure-query-parms"></a>Query parameters<a class="edit_me edit_me_private" rel="nofollow" title="Editing on GitHub is available to Elastic" href="https://github.com/elastic/elasticsearch/edit/7.7/docs/reference/ml/anomaly-detection/apis/find-file-structure.asciidoc">edit</a>
</h3>
</div></div></div>
<div class="variablelist">
<dl class="variablelist">
<dt>
<span class="term">
<code class="literal">charset</code>
</span>
</dt>
<dd>
(Optional, string) The file’s character set. It must be a character set that
is supported by the JVM that Elasticsearch uses. For example, <code class="literal">UTF-8</code>, <code class="literal">UTF-16LE</code>,
<code class="literal">windows-1252</code>, or <code class="literal">EUC-JP</code>. If this parameter is not specified, the structure
finder chooses an appropriate character set.
</dd>
<dt>
<span class="term">
<code class="literal">column_names</code>
</span>
</dt>
<dd>
(Optional, string) If you have set <code class="literal">format</code> to <code class="literal">delimited</code>, you can specify
the column names in a comma-separated list. If this parameter is not specified,
the structure finder uses the column names from the header row of the file. If
the file does not have a header role, columns are named "column1", "column2",
"column3", etc.
</dd>
<dt>
<span class="term">
<code class="literal">delimiter</code>
</span>
</dt>
<dd>
(Optional, string) If you have set <code class="literal">format</code> to <code class="literal">delimited</code>, you can specify
the character used to delimit the values in each row. Only a single character
is supported; the delimiter cannot have multiple characters. If this parameter
is not specified, the structure finder considers the following possibilities:
comma, tab, semi-colon, and pipe (<code class="literal">|</code>).
</dd>
<dt>
<span class="term">
<code class="literal">explain</code>
</span>
</dt>
<dd>
(Optional, boolean) If this parameter is set to <code class="literal">true</code>, the response includes
a field named <code class="literal">explanation</code>, which is an array of strings that indicate how
the structure finder produced its result. The default value is <code class="literal">false</code>.
</dd>
<dt>
<span class="term">
<code class="literal">format</code>
</span>
</dt>
<dd>
(Optional, string) The high level structure of the file. Valid values are
<code class="literal">ndjson</code>, <code class="literal">xml</code>, <code class="literal">delimited</code>, and <code class="literal">semi_structured_text</code>. If this parameter is
not specified, the structure finder chooses one.
</dd>
<dt>
<span class="term">
<code class="literal">grok_pattern</code>
</span>
</dt>
<dd>
(Optional, string) If you have set <code class="literal">format</code> to <code class="literal">semi_structured_text</code>, you can
specify a Grok pattern that is used to extract fields from every message in
the file. The name of the timestamp field in the Grok pattern must match what
is specified in the <code class="literal">timestamp_field</code> parameter. If that parameter is not
specified, the name of the timestamp field in the Grok pattern must match
"timestamp". If <code class="literal">grok_pattern</code> is not specified, the structure finder creates
a Grok pattern.
</dd>
<dt>
<span class="term">
<code class="literal">has_header_row</code>
</span>
</dt>
<dd>
(Optional, boolean) If you have set <code class="literal">format</code> to <code class="literal">delimited</code>, you can use this
parameter to indicate whether the column names are in the first row of the
file. If this parameter is not specified, the structure finder guesses based
on the similarity of the first row of the file to other rows.
</dd>
<dt>
<span class="term">
<code class="literal">line_merge_size_limit</code>
</span>
</dt>
<dd>
(Optional, unsigned integer) The maximum number of characters in a message
when lines are merged to form messages while analyzing semi-structured files.
The default is <code class="literal">10000</code>. If you have extremely long messages you may need to
increase this, but be aware that this may lead to very long processing times
if the way to group lines into messages is misdetected.
</dd>
<dt>
<span class="term">
<code class="literal">lines_to_sample</code>
</span>
</dt>
<dd>
<p>
(Optional, unsigned integer) The number of lines to include in the structural
analysis, starting from the beginning of the file. The minimum is 2; the
default is <code class="literal">1000</code>. If the value of this parameter is greater than the number
of lines in the file, the analysis proceeds (as long as there are at least two
lines in the file) for all of the lines.<br>
</p>
<div class="note admon">
<div class="icon"></div>
<div class="admon_content">
<p>The number of lines and the variation of the lines affects the speed of
the analysis. For example, if you upload a log file where the first 1000 lines
are all variations on the same message, the analysis will find more commonality
than would be seen with a bigger sample. If possible, however, it is more
efficient to upload a sample file with more variety in the first 1000 lines than
to request analysis of 100000 lines to achieve some variety.</p>
</div>
</div>
</dd>
<dt>
<span class="term">
<code class="literal">quote</code>
</span>
</dt>
<dd>
(Optional, string) If you have set <code class="literal">format</code> to <code class="literal">delimited</code>, you can specify
the character used to quote the values in each row if they contain newlines or
the delimiter character. Only a single character is supported. If this
parameter is not specified, the default value is a double quote (<code class="literal">"</code>). If your
delimited file format does not use quoting, a workaround is to set this
argument to a character that does not appear anywhere in the sample.
</dd>
<dt>
<span class="term">
<code class="literal">should_trim_fields</code>
</span>
</dt>
<dd>
(Optional, boolean) If you have set <code class="literal">format</code> to <code class="literal">delimited</code>, you can specify
whether values between delimiters should have whitespace trimmed from them. If
this parameter is not specified and the delimiter is pipe (<code class="literal">|</code>), the default
value is <code class="literal">true</code>. Otherwise, the default value is <code class="literal">false</code>.
</dd>
<dt>
<span class="term">
<code class="literal">timeout</code>
</span>
</dt>
<dd>
(Optional, <a class="xref" href="common-options.html#time-units" title="Time units">time units</a>) Sets the maximum amount of time that the
structure analysis make take. If the analysis is still running when the
timeout expires then it will be aborted. The default value is 25 seconds.
</dd>
<dt>
<span class="term">
<code class="literal">timestamp_field</code>
</span>
</dt>
<dd>
<p>
(Optional, string) The name of the field that contains the primary timestamp
of each record in the file. In particular, if the file were ingested into an
index, this is the field that would be used to populate the <code class="literal">@timestamp</code> field.
</p>
<p>If the <code class="literal">format</code> is <code class="literal">semi_structured_text</code>, this field must match the name of the
appropriate extraction in the <code class="literal">grok_pattern</code>. Therefore, for semi-structured
file formats, it is best not to specify this parameter unless <code class="literal">grok_pattern</code> is
also specified.</p>
<p>For structured file formats, if you specify this parameter, the field must exist
within the file.</p>
<p>If this parameter is not specified, the structure finder makes a decision about
which field (if any) is the primary timestamp field. For structured file
formats, it is not compulsory to have a timestamp in the file.</p>
</dd>
<dt>
<span class="term">
<code class="literal">timestamp_format</code>
</span>
</dt>
<dd>
<p>
(Optional, string) The Java time format of the timestamp field in the file.
</p>
<p>Only a subset of Java time format letter groups are supported:</p>
<div class="ulist itemizedlist">
<ul class="itemizedlist">
<li class="listitem">
<code class="literal">a</code>
</li>
<li class="listitem">
<code class="literal">d</code>
</li>
<li class="listitem">
<code class="literal">dd</code>
</li>
<li class="listitem">
<code class="literal">EEE</code>
</li>
<li class="listitem">
<code class="literal">EEEE</code>
</li>
<li class="listitem">
<code class="literal">H</code>
</li>
<li class="listitem">
<code class="literal">HH</code>
</li>
<li class="listitem">
<code class="literal">h</code>
</li>
<li class="listitem">
<code class="literal">M</code>
</li>
<li class="listitem">
<code class="literal">MM</code>
</li>
<li class="listitem">
<code class="literal">MMM</code>
</li>
<li class="listitem">
<code class="literal">MMMM</code>
</li>
<li class="listitem">
<code class="literal">mm</code>
</li>
<li class="listitem">
<code class="literal">ss</code>
</li>
<li class="listitem">
<code class="literal">XX</code>
</li>
<li class="listitem">
<code class="literal">XXX</code>
</li>
<li class="listitem">
<code class="literal">yy</code>
</li>
<li class="listitem">
<code class="literal">yyyy</code>
</li>
<li class="listitem">
<code class="literal">zzz</code>
</li>
</ul>
</div>
<p>Additionally <code class="literal">S</code> letter groups (fractional seconds) of length one to nine are
supported providing they occur after <code class="literal">ss</code> and separated from the <code class="literal">ss</code> by a <code class="literal">.</code>,
<code class="literal">,</code> or <code class="literal">:</code>. Spacing and punctuation is also permitted with the exception of <code class="literal">?</code>,
newline and carriage return, together with literal text enclosed in single
quotes. For example, <code class="literal">MM/dd HH.mm.ss,SSSSSS 'in' yyyy</code> is a valid override
format.</p>
<p>One valuable use case for this parameter is when the format is semi-structured
text, there are multiple timestamp formats in the file, and you know which
format corresponds to the primary timestamp, but you do not want to specify the
full <code class="literal">grok_pattern</code>. Another is when the timestamp format is one that the
structure finder does not consider by default.</p>
<p>If this parameter is not specified, the structure finder chooses the best
format from a built-in set.</p>
<p>The following table provides the appropriate <code class="literal">timeformat</code> values for some example timestamps:</p>
<div class="informaltable">
<table border="1" cellpadding="4px">
<colgroup>
<col class="col_1">
<col class="col_2">
</colgroup>
<thead>
<tr>
<th align="left" valign="top">Timeformat</th>
<th align="left" valign="top">Presentation</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top"><p>yyyy-MM-dd HH:mm:ssZ</p></td>
<td align="left" valign="top"><p>2019-04-20 13:15:22+0000</p></td>
</tr>
<tr>
<td align="left" valign="top"><p>EEE, d MMM yyyy HH:mm:ss Z</p></td>
<td align="left" valign="top"><p>Sat, 20 Apr 2019 13:15:22 +0000</p></td>
</tr>
<tr>
<td align="left" valign="top"><p>dd.MM.yy HH:mm:ss.SSS</p></td>
<td align="left" valign="top"><p>20.04.19 13:15:22.285</p></td>
</tr>
</tbody>
</table>
</div>
<p>See
<a href="https://docs.oracle.com/javase/8/docs/api/java/time/format/DateTimeFormatter.html" class="ulink" target="_top">the Java date/time format documentation</a>
for more information about date and time format syntax.</p>
</dd>
</dl>
</div>
</div>

<div class="section">
<div class="titlepage"><div><div>
<h3 class="title">
<a id="ml-find-file-structure-request-body"></a>Request body<a class="edit_me edit_me_private" rel="nofollow" title="Editing on GitHub is available to Elastic" href="https://github.com/elastic/elasticsearch/edit/7.7/docs/reference/ml/anomaly-detection/apis/find-file-structure.asciidoc">edit</a>
</h3>
</div></div></div>
<p>The text file that you want to analyze. It must contain data that is suitable to
be ingested into Elasticsearch. It does not need to be in JSON format and it does not
need to be UTF-8 encoded. The size is limited to the Elasticsearch HTTP receive buffer
size, which defaults to 100 Mb.</p>
</div>

<div class="section">
<div class="titlepage"><div><div>
<h3 class="title">
<a id="ml-find-file-structure-examples"></a>Examples<a class="edit_me edit_me_private" rel="nofollow" title="Editing on GitHub is available to Elastic" href="https://github.com/elastic/elasticsearch/edit/7.7/docs/reference/ml/anomaly-detection/apis/find-file-structure.asciidoc">edit</a>
</h3>
</div></div></div>
<div class="section">
<div class="titlepage"><div><div>
<h4 class="title">
<a id="ml-find-file-structure-example-nld-json"></a>Ingesting newline-delimited JSON<a class="edit_me edit_me_private" rel="nofollow" title="Editing on GitHub is available to Elastic" href="https://github.com/elastic/elasticsearch/edit/7.7/docs/reference/ml/anomaly-detection/apis/find-file-structure.asciidoc">edit</a>
</h4>
</div></div></div>
<p>Suppose you have a newline-delimited JSON file that contains information about
some books. You can send the contents to the <code class="literal">find_file_structure</code> endpoint:</p>
<div class="pre_wrapper lang-console">
<pre class="programlisting prettyprint lang-console">POST _ml/find_file_structure
{"name": "Leviathan Wakes", "author": "James S.A. Corey", "release_date": "2011-06-02", "page_count": 561}
{"name": "Hyperion", "author": "Dan Simmons", "release_date": "1989-05-26", "page_count": 482}
{"name": "Dune", "author": "Frank Herbert", "release_date": "1965-06-01", "page_count": 604}
{"name": "Dune Messiah", "author": "Frank Herbert", "release_date": "1969-10-15", "page_count": 331}
{"name": "Children of Dune", "author": "Frank Herbert", "release_date": "1976-04-21", "page_count": 408}
{"name": "God Emperor of Dune", "author": "Frank Herbert", "release_date": "1981-05-28", "page_count": 454}
{"name": "Consider Phlebas", "author": "Iain M. Banks", "release_date": "1987-04-23", "page_count": 471}
{"name": "Pandora's Star", "author": "Peter F. Hamilton", "release_date": "2004-03-02", "page_count": 768}
{"name": "Revelation Space", "author": "Alastair Reynolds", "release_date": "2000-03-15", "page_count": 585}
{"name": "A Fire Upon the Deep", "author": "Vernor Vinge", "release_date": "1992-06-01", "page_count": 613}
{"name": "Ender's Game", "author": "Orson Scott Card", "release_date": "1985-06-01", "page_count": 324}
{"name": "1984", "author": "George Orwell", "release_date": "1985-06-01", "page_count": 328}
{"name": "Fahrenheit 451", "author": "Ray Bradbury", "release_date": "1953-10-15", "page_count": 227}
{"name": "Brave New World", "author": "Aldous Huxley", "release_date": "1932-06-01", "page_count": 268}
{"name": "Foundation", "author": "Isaac Asimov", "release_date": "1951-06-01", "page_count": 224}
{"name": "The Giver", "author": "Lois Lowry", "release_date": "1993-04-26", "page_count": 208}
{"name": "Slaughterhouse-Five", "author": "Kurt Vonnegut", "release_date": "1969-06-01", "page_count": 275}
{"name": "The Hitchhiker's Guide to the Galaxy", "author": "Douglas Adams", "release_date": "1979-10-12", "page_count": 180}
{"name": "Snow Crash", "author": "Neal Stephenson", "release_date": "1992-06-01", "page_count": 470}
{"name": "Neuromancer", "author": "William Gibson", "release_date": "1984-07-01", "page_count": 271}
{"name": "The Handmaid's Tale", "author": "Margaret Atwood", "release_date": "1985-06-01", "page_count": 311}
{"name": "Starship Troopers", "author": "Robert A. Heinlein", "release_date": "1959-12-01", "page_count": 335}
{"name": "The Left Hand of Darkness", "author": "Ursula K. Le Guin", "release_date": "1969-06-01", "page_count": 304}
{"name": "The Moon is a Harsh Mistress", "author": "Robert A. Heinlein", "release_date": "1966-04-01", "page_count": 288}</pre>
</div>
<div class="console_widget" data-snippet="snippets/1814.console"></div>
<p>If the request does not encounter errors, you receive the following result:</p>
<div class="pre_wrapper lang-console-result">
<pre class="programlisting prettyprint lang-console-result">{
  "num_lines_analyzed" : 24, <a id="CO590-1"></a><i class="conum" data-value="1"></i>
  "num_messages_analyzed" : 24, <a id="CO590-2"></a><i class="conum" data-value="2"></i>
  "sample_start" : "{\"name\": \"Leviathan Wakes\", \"author\": \"James S.A. Corey\", \"release_date\": \"2011-06-02\", \"page_count\": 561}\n{\"name\": \"Hyperion\", \"author\": \"Dan Simmons\", \"release_date\": \"1989-05-26\", \"page_count\": 482}\n", <a id="CO590-3"></a><i class="conum" data-value="3"></i>
  "charset" : "UTF-8", <a id="CO590-4"></a><i class="conum" data-value="4"></i>
  "has_byte_order_marker" : false, <a id="CO590-5"></a><i class="conum" data-value="5"></i>
  "format" : "ndjson", <a id="CO590-6"></a><i class="conum" data-value="6"></i>
  "timestamp_field" : "release_date", <a id="CO590-7"></a><i class="conum" data-value="7"></i>
  "joda_timestamp_formats" : [ <a id="CO590-8"></a><i class="conum" data-value="8"></i>
    "ISO8601"
  ],
  "java_timestamp_formats" : [ <a id="CO590-9"></a><i class="conum" data-value="9"></i>
    "ISO8601"
  ],
  "need_client_timezone" : true, <a id="CO590-10"></a><i class="conum" data-value="10"></i>
  "mappings" : { <a id="CO590-11"></a><i class="conum" data-value="11"></i>
    "@timestamp" : {
      "type" : "date"
    },
    "author" : {
      "type" : "keyword"
    },
    "name" : {
      "type" : "keyword"
    },
    "page_count" : {
      "type" : "long"
    },
    "release_date" : {
      "type" : "date",
      "format" : "iso8601"
    }
  },
  "ingest_pipeline" : {
    "description" : "Ingest pipeline created by file structure finder",
    "processors" : [
      {
        "date" : {
          "field" : "release_date",
          "timezone" : "{{ event.timezone }}",
          "formats" : [
            "ISO8601"
          ]
        }
      }
    ]
  },
  "field_stats" : { <a id="CO590-12"></a><i class="conum" data-value="12"></i>
    "author" : {
      "count" : 24,
      "cardinality" : 20,
      "top_hits" : [
        {
          "value" : "Frank Herbert",
          "count" : 4
        },
        {
          "value" : "Robert A. Heinlein",
          "count" : 2
        },
        {
          "value" : "Alastair Reynolds",
          "count" : 1
        },
        {
          "value" : "Aldous Huxley",
          "count" : 1
        },
        {
          "value" : "Dan Simmons",
          "count" : 1
        },
        {
          "value" : "Douglas Adams",
          "count" : 1
        },
        {
          "value" : "George Orwell",
          "count" : 1
        },
        {
          "value" : "Iain M. Banks",
          "count" : 1
        },
        {
          "value" : "Isaac Asimov",
          "count" : 1
        },
        {
          "value" : "James S.A. Corey",
          "count" : 1
        }
      ]
    },
    "name" : {
      "count" : 24,
      "cardinality" : 24,
      "top_hits" : [
        {
          "value" : "1984",
          "count" : 1
        },
        {
          "value" : "A Fire Upon the Deep",
          "count" : 1
        },
        {
          "value" : "Brave New World",
          "count" : 1
        },
        {
          "value" : "Children of Dune",
          "count" : 1
        },
        {
          "value" : "Consider Phlebas",
          "count" : 1
        },
        {
          "value" : "Dune",
          "count" : 1
        },
        {
          "value" : "Dune Messiah",
          "count" : 1
        },
        {
          "value" : "Ender's Game",
          "count" : 1
        },
        {
          "value" : "Fahrenheit 451",
          "count" : 1
        },
        {
          "value" : "Foundation",
          "count" : 1
        }
      ]
    },
    "page_count" : {
      "count" : 24,
      "cardinality" : 24,
      "min_value" : 180,
      "max_value" : 768,
      "mean_value" : 387.0833333333333,
      "median_value" : 329.5,
      "top_hits" : [
        {
          "value" : 180,
          "count" : 1
        },
        {
          "value" : 208,
          "count" : 1
        },
        {
          "value" : 224,
          "count" : 1
        },
        {
          "value" : 227,
          "count" : 1
        },
        {
          "value" : 268,
          "count" : 1
        },
        {
          "value" : 271,
          "count" : 1
        },
        {
          "value" : 275,
          "count" : 1
        },
        {
          "value" : 288,
          "count" : 1
        },
        {
          "value" : 304,
          "count" : 1
        },
        {
          "value" : 311,
          "count" : 1
        }
      ]
    },
    "release_date" : {
      "count" : 24,
      "cardinality" : 20,
      "earliest" : "1932-06-01",
      "latest" : "2011-06-02",
      "top_hits" : [
        {
          "value" : "1985-06-01",
          "count" : 3
        },
        {
          "value" : "1969-06-01",
          "count" : 2
        },
        {
          "value" : "1992-06-01",
          "count" : 2
        },
        {
          "value" : "1932-06-01",
          "count" : 1
        },
        {
          "value" : "1951-06-01",
          "count" : 1
        },
        {
          "value" : "1953-10-15",
          "count" : 1
        },
        {
          "value" : "1959-12-01",
          "count" : 1
        },
        {
          "value" : "1965-06-01",
          "count" : 1
        },
        {
          "value" : "1966-04-01",
          "count" : 1
        },
        {
          "value" : "1969-10-15",
          "count" : 1
        }
      ]
    }
  }
}</pre>
</div>
<div class="calloutlist">
<table border="0" summary="Callout list">
<tr>
<td align="left" valign="top" width="5%">
<p><a href="#CO590-1"><i class="conum" data-value="1"></i></a></p>
</td>
<td align="left" valign="top">
<p><code class="literal">num_lines_analyzed</code> indicates how many lines of the file were analyzed.</p>
</td>
</tr>
<tr>
<td align="left" valign="top" width="5%">
<p><a href="#CO590-2"><i class="conum" data-value="2"></i></a></p>
</td>
<td align="left" valign="top">
<p><code class="literal">num_messages_analyzed</code> indicates how many distinct messages the lines contained.
For NDJSON, this value is the same as <code class="literal">num_lines_analyzed</code>. For other file
formats, messages can span several lines.</p>
</td>
</tr>
<tr>
<td align="left" valign="top" width="5%">
<p><a href="#CO590-3"><i class="conum" data-value="3"></i></a></p>
</td>
<td align="left" valign="top">
<p><code class="literal">sample_start</code> reproduces the first two messages in the file verbatim. This
may help to diagnose parse errors or accidental uploads of the wrong file.</p>
</td>
</tr>
<tr>
<td align="left" valign="top" width="5%">
<p><a href="#CO590-4"><i class="conum" data-value="4"></i></a></p>
</td>
<td align="left" valign="top">
<p><code class="literal">charset</code> indicates the character encoding used to parse the file.</p>
</td>
</tr>
<tr>
<td align="left" valign="top" width="5%">
<p><a href="#CO590-5"><i class="conum" data-value="5"></i></a></p>
</td>
<td align="left" valign="top">
<p>For UTF character encodings, <code class="literal">has_byte_order_marker</code> indicates whether the
file begins with a byte order marker.</p>
</td>
</tr>
<tr>
<td align="left" valign="top" width="5%">
<p><a href="#CO590-6"><i class="conum" data-value="6"></i></a></p>
</td>
<td align="left" valign="top">
<p><code class="literal">format</code> is one of <code class="literal">ndjson</code>, <code class="literal">xml</code>, <code class="literal">delimited</code> or <code class="literal">semi_structured_text</code>.</p>
</td>
</tr>
<tr>
<td align="left" valign="top" width="5%">
<p><a href="#CO590-7"><i class="conum" data-value="7"></i></a></p>
</td>
<td align="left" valign="top">
<p>The <code class="literal">timestamp_field</code> names the field considered most likely to be the
primary timestamp of each document.</p>
</td>
</tr>
<tr>
<td align="left" valign="top" width="5%">
<p><a href="#CO590-8"><i class="conum" data-value="8"></i></a></p>
</td>
<td align="left" valign="top">
<p><code class="literal">joda_timestamp_formats</code> are used to tell Logstash how to parse timestamps.</p>
</td>
</tr>
<tr>
<td align="left" valign="top" width="5%">
<p><a href="#CO590-9"><i class="conum" data-value="9"></i></a></p>
</td>
<td align="left" valign="top">
<p><code class="literal">java_timestamp_formats</code> are the Java time formats recognized in the time
fields. Elasticsearch mappings and Ingest pipeline use this format.</p>
</td>
</tr>
<tr>
<td align="left" valign="top" width="5%">
<p><a href="#CO590-10"><i class="conum" data-value="10"></i></a></p>
</td>
<td align="left" valign="top">
<p>If a timestamp format is detected that does not include a timezone,
<code class="literal">need_client_timezone</code> will be <code class="literal">true</code>. The server that parses the file must
therefore be told the correct timezone by the client.</p>
</td>
</tr>
<tr>
<td align="left" valign="top" width="5%">
<p><a href="#CO590-11"><i class="conum" data-value="11"></i></a></p>
</td>
<td align="left" valign="top">
<p><code class="literal">mappings</code> contains some suitable mappings for an index into which the data
could be ingested. In this case, the <code class="literal">release_date</code> field has been given a
<code class="literal">keyword</code> type as it is not considered specific enough to convert to the
<code class="literal">date</code> type.</p>
</td>
</tr>
<tr>
<td align="left" valign="top" width="5%">
<p><a href="#CO590-12"><i class="conum" data-value="12"></i></a></p>
</td>
<td align="left" valign="top">
<p><code class="literal">field_stats</code> contains the most common values of each field, plus basic
numeric statistics for the numeric <code class="literal">page_count</code> field. This information
may provide clues that the data needs to be cleaned or transformed prior
to use by other machine learning functionality.</p>
</td>
</tr>
</table>
</div>
</div>

<div class="section">
<div class="titlepage"><div><div>
<h4 class="title">
<a id="ml-find-file-structure-example-nyc"></a>Finding the structure of NYC yellow cab example data<a class="edit_me edit_me_private" rel="nofollow" title="Editing on GitHub is available to Elastic" href="https://github.com/elastic/elasticsearch/edit/7.7/docs/reference/ml/anomaly-detection/apis/find-file-structure.asciidoc">edit</a>
</h4>
</div></div></div>
<p>The next example shows how it’s possible to find the structure of some New York
City yellow cab trip data. The first <code class="literal">curl</code> command downloads the data, the
first 20000 lines of which are then piped into the <code class="literal">find_file_structure</code>
endpoint. The <code class="literal">lines_to_sample</code> query parameter of the endpoint is set to 20000
to match what is specified in the <code class="literal">head</code> command.</p>
<div class="pre_wrapper lang-js">
<pre class="programlisting prettyprint lang-js">curl -s "s3.amazonaws.com/nyc-tlc/trip+data/yellow_tripdata_2018-06.csv" | head -20000 | curl -s -H "Content-Type: application/json" -XPOST "localhost:9200/_ml/find_file_structure?pretty&amp;lines_to_sample=20000" -T -</pre>
</div>
<div class="note admon">
<div class="icon"></div>
<div class="admon_content">
<p>The <code class="literal">Content-Type: application/json</code> header must be set even though in
this case the data is not JSON. (Alternatively the <code class="literal">Content-Type</code> can be set
to any other supported by Elasticsearch, but it must be set.)</p>
</div>
</div>
<p>If the request does not encounter errors, you receive the following result:</p>
<div class="pre_wrapper lang-js">
<pre class="programlisting prettyprint lang-js">{
  "num_lines_analyzed" : 20000,
  "num_messages_analyzed" : 19998, <a id="CO591-1"></a><i class="conum" data-value="1"></i>
  "sample_start" : "VendorID,tpep_pickup_datetime,tpep_dropoff_datetime,passenger_count,trip_distance,RatecodeID,store_and_fwd_flag,PULocationID,DOLocationID,payment_type,fare_amount,extra,mta_tax,tip_amount,tolls_amount,improvement_surcharge,total_amount\n\n1,2018-06-01 00:15:40,2018-06-01 00:16:46,1,.00,1,N,145,145,2,3,0.5,0.5,0,0,0.3,4.3\n",
  "charset" : "UTF-8",
  "has_byte_order_marker" : false,
  "format" : "delimited", <a id="CO591-2"></a><i class="conum" data-value="2"></i>
  "multiline_start_pattern" : "^.*?,\"?\\d{4}-\\d{2}-\\d{2}[T ]\\d{2}:\\d{2}",
  "exclude_lines_pattern" : "^\"?VendorID\"?,\"?tpep_pickup_datetime\"?,\"?tpep_dropoff_datetime\"?,\"?passenger_count\"?,\"?trip_distance\"?,\"?RatecodeID\"?,\"?store_and_fwd_flag\"?,\"?PULocationID\"?,\"?DOLocationID\"?,\"?payment_type\"?,\"?fare_amount\"?,\"?extra\"?,\"?mta_tax\"?,\"?tip_amount\"?,\"?tolls_amount\"?,\"?improvement_surcharge\"?,\"?total_amount\"?",
  "column_names" : [ <a id="CO591-3"></a><i class="conum" data-value="3"></i>
    "VendorID",
    "tpep_pickup_datetime",
    "tpep_dropoff_datetime",
    "passenger_count",
    "trip_distance",
    "RatecodeID",
    "store_and_fwd_flag",
    "PULocationID",
    "DOLocationID",
    "payment_type",
    "fare_amount",
    "extra",
    "mta_tax",
    "tip_amount",
    "tolls_amount",
    "improvement_surcharge",
    "total_amount"
  ],
  "has_header_row" : true, <a id="CO591-4"></a><i class="conum" data-value="4"></i>
  "delimiter" : ",", <a id="CO591-5"></a><i class="conum" data-value="5"></i>
  "quote" : "\"", <a id="CO591-6"></a><i class="conum" data-value="6"></i>
  "timestamp_field" : "tpep_pickup_datetime", <a id="CO591-7"></a><i class="conum" data-value="7"></i>
  "joda_timestamp_formats" : [ <a id="CO591-8"></a><i class="conum" data-value="8"></i>
    "YYYY-MM-dd HH:mm:ss"
  ],
  "java_timestamp_formats" : [ <a id="CO591-9"></a><i class="conum" data-value="9"></i>
    "yyyy-MM-dd HH:mm:ss"
  ],
  "need_client_timezone" : true, <a id="CO591-10"></a><i class="conum" data-value="10"></i>
  "mappings" : {
    "@timestamp" : {
      "type" : "date"
    },
    "DOLocationID" : {
      "type" : "long"
    },
    "PULocationID" : {
      "type" : "long"
    },
    "RatecodeID" : {
      "type" : "long"
    },
    "VendorID" : {
      "type" : "long"
    },
    "extra" : {
      "type" : "double"
    },
    "fare_amount" : {
      "type" : "double"
    },
    "improvement_surcharge" : {
      "type" : "double"
    },
    "mta_tax" : {
      "type" : "double"
    },
    "passenger_count" : {
      "type" : "long"
    },
    "payment_type" : {
      "type" : "long"
    },
    "store_and_fwd_flag" : {
      "type" : "keyword"
    },
    "tip_amount" : {
      "type" : "double"
    },
    "tolls_amount" : {
      "type" : "double"
    },
    "total_amount" : {
      "type" : "double"
    },
    "tpep_dropoff_datetime" : {
      "type" : "date",
      "format" : "yyyy-MM-dd HH:mm:ss"
    },
    "tpep_pickup_datetime" : {
      "type" : "date",
      "format" : "yyyy-MM-dd HH:mm:ss"
    },
    "trip_distance" : {
      "type" : "double"
    }
  },
  "ingest_pipeline" : {
    "description" : "Ingest pipeline created by file structure finder",
    "processors" : [
      {
        "csv" : {
          "field" : "message",
          "target_fields" : [
            "VendorID",
            "tpep_pickup_datetime",
            "tpep_dropoff_datetime",
            "passenger_count",
            "trip_distance",
            "RatecodeID",
            "store_and_fwd_flag",
            "PULocationID",
            "DOLocationID",
            "payment_type",
            "fare_amount",
            "extra",
            "mta_tax",
            "tip_amount",
            "tolls_amount",
            "improvement_surcharge",
            "total_amount"
          ]
        }
      },
      {
        "date" : {
          "field" : "tpep_pickup_datetime",
          "timezone" : "{{ event.timezone }}",
          "formats" : [
            "yyyy-MM-dd HH:mm:ss"
          ]
        }
      },
      {
        "convert" : {
          "field" : "DOLocationID",
          "type" : "long"
        }
      },
      {
        "convert" : {
          "field" : "PULocationID",
          "type" : "long"
        }
      },
      {
        "convert" : {
          "field" : "RatecodeID",
          "type" : "long"
        }
      },
      {
        "convert" : {
          "field" : "VendorID",
          "type" : "long"
        }
      },
      {
        "convert" : {
          "field" : "extra",
          "type" : "double"
        }
      },
      {
        "convert" : {
          "field" : "fare_amount",
          "type" : "double"
        }
      },
      {
        "convert" : {
          "field" : "improvement_surcharge",
          "type" : "double"
        }
      },
      {
        "convert" : {
          "field" : "mta_tax",
          "type" : "double"
        }
      },
      {
        "convert" : {
          "field" : "passenger_count",
          "type" : "long"
        }
      },
      {
        "convert" : {
          "field" : "payment_type",
          "type" : "long"
        }
      },
      {
        "convert" : {
          "field" : "tip_amount",
          "type" : "double"
        }
      },
      {
        "convert" : {
          "field" : "tolls_amount",
          "type" : "double"
        }
      },
      {
        "convert" : {
          "field" : "total_amount",
          "type" : "double"
        }
      },
      {
        "convert" : {
          "field" : "trip_distance",
          "type" : "double"
        }
      },
      {
        "remove" : {
          "field" : "message"
        }
      }
    ]
  },
  "field_stats" : {
    "DOLocationID" : {
      "count" : 19998,
      "cardinality" : 240,
      "min_value" : 1,
      "max_value" : 265,
      "mean_value" : 150.26532653265312,
      "median_value" : 148,
      "top_hits" : [
        {
          "value" : 79,
          "count" : 760
        },
        {
          "value" : 48,
          "count" : 683
        },
        {
          "value" : 68,
          "count" : 529
        },
        {
          "value" : 170,
          "count" : 506
        },
        {
          "value" : 107,
          "count" : 468
        },
        {
          "value" : 249,
          "count" : 457
        },
        {
          "value" : 230,
          "count" : 441
        },
        {
          "value" : 186,
          "count" : 432
        },
        {
          "value" : 141,
          "count" : 409
        },
        {
          "value" : 263,
          "count" : 386
        }
      ]
    },
    "PULocationID" : {
      "count" : 19998,
      "cardinality" : 154,
      "min_value" : 1,
      "max_value" : 265,
      "mean_value" : 153.4042404240424,
      "median_value" : 148,
      "top_hits" : [
        {
          "value" : 79,
          "count" : 1067
        },
        {
          "value" : 230,
          "count" : 949
        },
        {
          "value" : 148,
          "count" : 940
        },
        {
          "value" : 132,
          "count" : 897
        },
        {
          "value" : 48,
          "count" : 853
        },
        {
          "value" : 161,
          "count" : 820
        },
        {
          "value" : 234,
          "count" : 750
        },
        {
          "value" : 249,
          "count" : 722
        },
        {
          "value" : 164,
          "count" : 663
        },
        {
          "value" : 114,
          "count" : 646
        }
      ]
    },
    "RatecodeID" : {
      "count" : 19998,
      "cardinality" : 5,
      "min_value" : 1,
      "max_value" : 5,
      "mean_value" : 1.0656565656565653,
      "median_value" : 1,
      "top_hits" : [
        {
          "value" : 1,
          "count" : 19311
        },
        {
          "value" : 2,
          "count" : 468
        },
        {
          "value" : 5,
          "count" : 195
        },
        {
          "value" : 4,
          "count" : 17
        },
        {
          "value" : 3,
          "count" : 7
        }
      ]
    },
    "VendorID" : {
      "count" : 19998,
      "cardinality" : 2,
      "min_value" : 1,
      "max_value" : 2,
      "mean_value" : 1.59005900590059,
      "median_value" : 2,
      "top_hits" : [
        {
          "value" : 2,
          "count" : 11800
        },
        {
          "value" : 1,
          "count" : 8198
        }
      ]
    },
    "extra" : {
      "count" : 19998,
      "cardinality" : 3,
      "min_value" : -0.5,
      "max_value" : 0.5,
      "mean_value" : 0.4815981598159816,
      "median_value" : 0.5,
      "top_hits" : [
        {
          "value" : 0.5,
          "count" : 19281
        },
        {
          "value" : 0,
          "count" : 698
        },
        {
          "value" : -0.5,
          "count" : 19
        }
      ]
    },
    "fare_amount" : {
      "count" : 19998,
      "cardinality" : 208,
      "min_value" : -100,
      "max_value" : 300,
      "mean_value" : 13.937719771977209,
      "median_value" : 9.5,
      "top_hits" : [
        {
          "value" : 6,
          "count" : 1004
        },
        {
          "value" : 6.5,
          "count" : 935
        },
        {
          "value" : 5.5,
          "count" : 909
        },
        {
          "value" : 7,
          "count" : 903
        },
        {
          "value" : 5,
          "count" : 889
        },
        {
          "value" : 7.5,
          "count" : 854
        },
        {
          "value" : 4.5,
          "count" : 802
        },
        {
          "value" : 8.5,
          "count" : 790
        },
        {
          "value" : 8,
          "count" : 789
        },
        {
          "value" : 9,
          "count" : 711
        }
      ]
    },
    "improvement_surcharge" : {
      "count" : 19998,
      "cardinality" : 3,
      "min_value" : -0.3,
      "max_value" : 0.3,
      "mean_value" : 0.29915991599159913,
      "median_value" : 0.3,
      "top_hits" : [
        {
          "value" : 0.3,
          "count" : 19964
        },
        {
          "value" : -0.3,
          "count" : 22
        },
        {
          "value" : 0,
          "count" : 12
        }
      ]
    },
    "mta_tax" : {
      "count" : 19998,
      "cardinality" : 3,
      "min_value" : -0.5,
      "max_value" : 0.5,
      "mean_value" : 0.4962246224622462,
      "median_value" : 0.5,
      "top_hits" : [
        {
          "value" : 0.5,
          "count" : 19868
        },
        {
          "value" : 0,
          "count" : 109
        },
        {
          "value" : -0.5,
          "count" : 21
        }
      ]
    },
    "passenger_count" : {
      "count" : 19998,
      "cardinality" : 7,
      "min_value" : 0,
      "max_value" : 6,
      "mean_value" : 1.6201620162016201,
      "median_value" : 1,
      "top_hits" : [
        {
          "value" : 1,
          "count" : 14219
        },
        {
          "value" : 2,
          "count" : 2886
        },
        {
          "value" : 5,
          "count" : 1047
        },
        {
          "value" : 3,
          "count" : 804
        },
        {
          "value" : 6,
          "count" : 523
        },
        {
          "value" : 4,
          "count" : 406
        },
        {
          "value" : 0,
          "count" : 113
        }
      ]
    },
    "payment_type" : {
      "count" : 19998,
      "cardinality" : 4,
      "min_value" : 1,
      "max_value" : 4,
      "mean_value" : 1.315631563156316,
      "median_value" : 1,
      "top_hits" : [
        {
          "value" : 1,
          "count" : 13936
        },
        {
          "value" : 2,
          "count" : 5857
        },
        {
          "value" : 3,
          "count" : 160
        },
        {
          "value" : 4,
          "count" : 45
        }
      ]
    },
    "store_and_fwd_flag" : {
      "count" : 19998,
      "cardinality" : 2,
      "top_hits" : [
        {
          "value" : "N",
          "count" : 19910
        },
        {
          "value" : "Y",
          "count" : 88
        }
      ]
    },
    "tip_amount" : {
      "count" : 19998,
      "cardinality" : 717,
      "min_value" : 0,
      "max_value" : 128,
      "mean_value" : 2.010959095909593,
      "median_value" : 1.45,
      "top_hits" : [
        {
          "value" : 0,
          "count" : 6917
        },
        {
          "value" : 1,
          "count" : 1178
        },
        {
          "value" : 2,
          "count" : 624
        },
        {
          "value" : 3,
          "count" : 248
        },
        {
          "value" : 1.56,
          "count" : 206
        },
        {
          "value" : 1.46,
          "count" : 205
        },
        {
          "value" : 1.76,
          "count" : 196
        },
        {
          "value" : 1.45,
          "count" : 195
        },
        {
          "value" : 1.36,
          "count" : 191
        },
        {
          "value" : 1.5,
          "count" : 187
        }
      ]
    },
    "tolls_amount" : {
      "count" : 19998,
      "cardinality" : 26,
      "min_value" : 0,
      "max_value" : 35,
      "mean_value" : 0.2729697969796978,
      "median_value" : 0,
      "top_hits" : [
        {
          "value" : 0,
          "count" : 19107
        },
        {
          "value" : 5.76,
          "count" : 791
        },
        {
          "value" : 10.5,
          "count" : 36
        },
        {
          "value" : 2.64,
          "count" : 21
        },
        {
          "value" : 11.52,
          "count" : 8
        },
        {
          "value" : 5.54,
          "count" : 4
        },
        {
          "value" : 8.5,
          "count" : 4
        },
        {
          "value" : 17.28,
          "count" : 4
        },
        {
          "value" : 2,
          "count" : 2
        },
        {
          "value" : 2.16,
          "count" : 2
        }
      ]
    },
    "total_amount" : {
      "count" : 19998,
      "cardinality" : 1267,
      "min_value" : -100.3,
      "max_value" : 389.12,
      "mean_value" : 17.499898989898995,
      "median_value" : 12.35,
      "top_hits" : [
        {
          "value" : 7.3,
          "count" : 478
        },
        {
          "value" : 8.3,
          "count" : 443
        },
        {
          "value" : 8.8,
          "count" : 420
        },
        {
          "value" : 6.8,
          "count" : 406
        },
        {
          "value" : 7.8,
          "count" : 405
        },
        {
          "value" : 6.3,
          "count" : 371
        },
        {
          "value" : 9.8,
          "count" : 368
        },
        {
          "value" : 5.8,
          "count" : 362
        },
        {
          "value" : 9.3,
          "count" : 332
        },
        {
          "value" : 10.3,
          "count" : 332
        }
      ]
    },
    "tpep_dropoff_datetime" : {
      "count" : 19998,
      "cardinality" : 9066,
      "earliest" : "2018-05-31 06:18:15",
      "latest" : "2018-06-02 02:25:44",
      "top_hits" : [
        {
          "value" : "2018-06-01 01:12:12",
          "count" : 10
        },
        {
          "value" : "2018-06-01 00:32:15",
          "count" : 9
        },
        {
          "value" : "2018-06-01 00:44:27",
          "count" : 9
        },
        {
          "value" : "2018-06-01 00:46:42",
          "count" : 9
        },
        {
          "value" : "2018-06-01 01:03:22",
          "count" : 9
        },
        {
          "value" : "2018-06-01 01:05:13",
          "count" : 9
        },
        {
          "value" : "2018-06-01 00:11:20",
          "count" : 8
        },
        {
          "value" : "2018-06-01 00:16:03",
          "count" : 8
        },
        {
          "value" : "2018-06-01 00:19:47",
          "count" : 8
        },
        {
          "value" : "2018-06-01 00:25:17",
          "count" : 8
        }
      ]
    },
    "tpep_pickup_datetime" : {
      "count" : 19998,
      "cardinality" : 8760,
      "earliest" : "2018-05-31 06:08:31",
      "latest" : "2018-06-02 01:21:21",
      "top_hits" : [
        {
          "value" : "2018-06-01 00:01:23",
          "count" : 12
        },
        {
          "value" : "2018-06-01 00:04:31",
          "count" : 10
        },
        {
          "value" : "2018-06-01 00:05:38",
          "count" : 10
        },
        {
          "value" : "2018-06-01 00:09:50",
          "count" : 10
        },
        {
          "value" : "2018-06-01 00:12:01",
          "count" : 10
        },
        {
          "value" : "2018-06-01 00:14:17",
          "count" : 10
        },
        {
          "value" : "2018-06-01 00:00:34",
          "count" : 9
        },
        {
          "value" : "2018-06-01 00:00:40",
          "count" : 9
        },
        {
          "value" : "2018-06-01 00:02:53",
          "count" : 9
        },
        {
          "value" : "2018-06-01 00:05:40",
          "count" : 9
        }
      ]
    },
    "trip_distance" : {
      "count" : 19998,
      "cardinality" : 1687,
      "min_value" : 0,
      "max_value" : 64.63,
      "mean_value" : 3.6521062106210715,
      "median_value" : 2.16,
      "top_hits" : [
        {
          "value" : 0.9,
          "count" : 335
        },
        {
          "value" : 0.8,
          "count" : 320
        },
        {
          "value" : 1.1,
          "count" : 316
        },
        {
          "value" : 0.7,
          "count" : 304
        },
        {
          "value" : 1.2,
          "count" : 303
        },
        {
          "value" : 1,
          "count" : 296
        },
        {
          "value" : 1.3,
          "count" : 280
        },
        {
          "value" : 1.5,
          "count" : 268
        },
        {
          "value" : 1.6,
          "count" : 268
        },
        {
          "value" : 0.6,
          "count" : 256
        }
      ]
    }
  }
}</pre>
</div>
<div class="calloutlist">
<table border="0" summary="Callout list">
<tr>
<td align="left" valign="top" width="5%">
<p><a href="#CO591-1"><i class="conum" data-value="1"></i></a></p>
</td>
<td align="left" valign="top">
<p><code class="literal">num_messages_analyzed</code> is 2 lower than <code class="literal">num_lines_analyzed</code> because only
data records count as messages. The first line contains the column names
and in this sample the second line is blank.</p>
</td>
</tr>
<tr>
<td align="left" valign="top" width="5%">
<p><a href="#CO591-2"><i class="conum" data-value="2"></i></a></p>
</td>
<td align="left" valign="top">
<p>Unlike the first example, in this case the <code class="literal">format</code> has been identified as
<code class="literal">delimited</code>.</p>
</td>
</tr>
<tr>
<td align="left" valign="top" width="5%">
<p><a href="#CO591-3"><i class="conum" data-value="3"></i></a></p>
</td>
<td align="left" valign="top">
<p>Because the <code class="literal">format</code> is <code class="literal">delimited</code>, the <code class="literal">column_names</code> field in the output
lists the column names in the order they appear in the sample.</p>
</td>
</tr>
<tr>
<td align="left" valign="top" width="5%">
<p><a href="#CO591-4"><i class="conum" data-value="4"></i></a></p>
</td>
<td align="left" valign="top">
<p><code class="literal">has_header_row</code> indicates that for this sample the column names were in
the first row of the sample. (If they hadn’t been then it would have been
a good idea to specify them in the <code class="literal">column_names</code> query parameter.)</p>
</td>
</tr>
<tr>
<td align="left" valign="top" width="5%">
<p><a href="#CO591-5"><i class="conum" data-value="5"></i></a></p>
</td>
<td align="left" valign="top">
<p>The <code class="literal">delimiter</code> for this sample is a comma, as it’s a CSV file.</p>
</td>
</tr>
<tr>
<td align="left" valign="top" width="5%">
<p><a href="#CO591-6"><i class="conum" data-value="6"></i></a></p>
</td>
<td align="left" valign="top">
<p>The <code class="literal">quote</code> character is the default double quote. (The structure finder
does not attempt to deduce any other quote character, so if you have a
delimited file that’s quoted with some other character you must specify it
using the <code class="literal">quote</code> query parameter.)</p>
</td>
</tr>
<tr>
<td align="left" valign="top" width="5%">
<p><a href="#CO591-7"><i class="conum" data-value="7"></i></a></p>
</td>
<td align="left" valign="top">
<p>The <code class="literal">timestamp_field</code> has been chosen to be <code class="literal">tpep_pickup_datetime</code>.
<code class="literal">tpep_dropoff_datetime</code> would work just as well, but <code class="literal">tpep_pickup_datetime</code>
was chosen because it comes first in the column order. If you prefer
<code class="literal">tpep_dropoff_datetime</code> then force it to be chosen using the
<code class="literal">timestamp_field</code> query parameter.</p>
</td>
</tr>
<tr>
<td align="left" valign="top" width="5%">
<p><a href="#CO591-8"><i class="conum" data-value="8"></i></a></p>
</td>
<td align="left" valign="top">
<p><code class="literal">joda_timestamp_formats</code> are used to tell Logstash how to parse timestamps.</p>
</td>
</tr>
<tr>
<td align="left" valign="top" width="5%">
<p><a href="#CO591-9"><i class="conum" data-value="9"></i></a></p>
</td>
<td align="left" valign="top">
<p><code class="literal">java_timestamp_formats</code> are the Java time formats recognized in the time
fields. Elasticsearch mappings and Ingest pipeline use this format.</p>
</td>
</tr>
<tr>
<td align="left" valign="top" width="5%">
<p><a href="#CO591-10"><i class="conum" data-value="10"></i></a></p>
</td>
<td align="left" valign="top">
<p>The timestamp format in this sample doesn’t specify a timezone, so to
accurately convert them to UTC timestamps to store in Elasticsearch it’s
necessary to supply the timezone they relate to. <code class="literal">need_client_timezone</code>
will be <code class="literal">false</code> for timestamp formats that include the timezone.</p>
</td>
</tr>
</table>
</div>
</div>

<div class="section">
<div class="titlepage"><div><div>
<h4 class="title">
<a id="ml-find-file-structure-example-timeout"></a>Setting the timeout parameter<a class="edit_me edit_me_private" rel="nofollow" title="Editing on GitHub is available to Elastic" href="https://github.com/elastic/elasticsearch/edit/7.7/docs/reference/ml/anomaly-detection/apis/find-file-structure.asciidoc">edit</a>
</h4>
</div></div></div>
<p>If you try to analyze a lot of data then the analysis will take a long time.
If you want to limit the amount of processing your Elasticsearch cluster performs for
a request, use the <code class="literal">timeout</code> query parameter. The analysis will be aborted and
an error returned when the timeout expires. For example, you can replace 20000
lines in the previous example with 200000 and set a 1 second timeout on the
analysis:</p>
<div class="pre_wrapper lang-js">
<pre class="programlisting prettyprint lang-js">curl -s "s3.amazonaws.com/nyc-tlc/trip+data/yellow_tripdata_2018-06.csv" | head -200000 | curl -s -H "Content-Type: application/json" -XPOST "localhost:9200/_ml/find_file_structure?pretty&amp;lines_to_sample=200000&amp;timeout=1s" -T -</pre>
</div>
<p>Unless you are using an incredibly fast computer you’ll receive a timeout error:</p>
<div class="pre_wrapper lang-js">
<pre class="programlisting prettyprint lang-js">{
  "error" : {
    "root_cause" : [
      {
        "type" : "timeout_exception",
        "reason" : "Aborting structure analysis during [delimited record parsing] as it has taken longer than the timeout of [1s]"
      }
    ],
    "type" : "timeout_exception",
    "reason" : "Aborting structure analysis during [delimited record parsing] as it has taken longer than the timeout of [1s]"
  },
  "status" : 500
}</pre>
</div>
<div class="note admon">
<div class="icon"></div>
<div class="admon_content">
<p>If you try the example above yourself you will note that the overall
running time of the <code class="literal">curl</code> commands is considerably longer than 1 second. This
is because it takes a while to download 200000 lines of CSV from the internet,
and the timeout is measured from the time this endpoint starts to process the
data.</p>
</div>
</div>
</div>

<div class="section">
<div class="titlepage"><div><div>
<h4 class="title">
<a id="ml-find-file-structure-example-eslog"></a>Analyzing Elasticsearch log files<a class="edit_me edit_me_private" rel="nofollow" title="Editing on GitHub is available to Elastic" href="https://github.com/elastic/elasticsearch/edit/7.7/docs/reference/ml/anomaly-detection/apis/find-file-structure.asciidoc">edit</a>
</h4>
</div></div></div>
<p>This is an example of analyzing Elasticsearch’s own log file:</p>
<div class="pre_wrapper lang-js">
<pre class="programlisting prettyprint lang-js">curl -s -H "Content-Type: application/json" -XPOST "localhost:9200/_ml/find_file_structure?pretty" -T "$ES_HOME/logs/elasticsearch.log"</pre>
</div>
<p>If the request does not encounter errors, the result will look something like
this:</p>
<div class="pre_wrapper lang-js">
<pre class="programlisting prettyprint lang-js">{
  "num_lines_analyzed" : 53,
  "num_messages_analyzed" : 53,
  "sample_start" : "[2018-09-27T14:39:28,518][INFO ][o.e.e.NodeEnvironment    ] [node-0] using [1] data paths, mounts [[/ (/dev/disk1)]], net usable_space [165.4gb], net total_space [464.7gb], types [hfs]\n[2018-09-27T14:39:28,521][INFO ][o.e.e.NodeEnvironment    ] [node-0] heap size [494.9mb], compressed ordinary object pointers [true]\n",
  "charset" : "UTF-8",
  "has_byte_order_marker" : false,
  "format" : "semi_structured_text", <a id="CO592-1"></a><i class="conum" data-value="1"></i>
  "multiline_start_pattern" : "^\\[\\b\\d{4}-\\d{2}-\\d{2}[T ]\\d{2}:\\d{2}", <a id="CO592-2"></a><i class="conum" data-value="2"></i>
  "grok_pattern" : "\\[%{TIMESTAMP_ISO8601:timestamp}\\]\\[%{LOGLEVEL:loglevel}.*", <a id="CO592-3"></a><i class="conum" data-value="3"></i>
  "timestamp_field" : "timestamp",
  "joda_timestamp_formats" : [
    "ISO8601"
  ],
  "java_timestamp_formats" : [
    "ISO8601"
  ],
  "need_client_timezone" : true,
  "mappings" : {
    "@timestamp" : {
      "type" : "date"
    },
    "loglevel" : {
      "type" : "keyword"
    },
    "message" : {
      "type" : "text"
    }
  },
  "ingest_pipeline" : {
    "description" : "Ingest pipeline created by file structure finder",
    "processors" : [
      {
        "grok" : {
          "field" : "message",
          "patterns" : [
            "\\[%{TIMESTAMP_ISO8601:timestamp}\\]\\[%{LOGLEVEL:loglevel}.*"
          ]
        }
      },
      {
        "date" : {
          "field" : "timestamp",
          "timezone" : "{{ event.timezone }}",
          "formats" : [
            "ISO8601"
          ]
        }
      },
      {
        "remove" : {
          "field" : "timestamp"
        }
      }
    ]
  },
  "field_stats" : {
    "loglevel" : {
      "count" : 53,
      "cardinality" : 3,
      "top_hits" : [
        {
          "value" : "INFO",
          "count" : 51
        },
        {
          "value" : "DEBUG",
          "count" : 1
        },
        {
          "value" : "WARN",
          "count" : 1
        }
      ]
    },
    "timestamp" : {
      "count" : 53,
      "cardinality" : 28,
      "earliest" : "2018-09-27T14:39:28,518",
      "latest" : "2018-09-27T14:39:37,012",
      "top_hits" : [
        {
          "value" : "2018-09-27T14:39:29,859",
          "count" : 10
        },
        {
          "value" : "2018-09-27T14:39:29,860",
          "count" : 9
        },
        {
          "value" : "2018-09-27T14:39:29,858",
          "count" : 6
        },
        {
          "value" : "2018-09-27T14:39:28,523",
          "count" : 3
        },
        {
          "value" : "2018-09-27T14:39:34,234",
          "count" : 2
        },
        {
          "value" : "2018-09-27T14:39:28,518",
          "count" : 1
        },
        {
          "value" : "2018-09-27T14:39:28,521",
          "count" : 1
        },
        {
          "value" : "2018-09-27T14:39:28,522",
          "count" : 1
        },
        {
          "value" : "2018-09-27T14:39:29,861",
          "count" : 1
        },
        {
          "value" : "2018-09-27T14:39:32,786",
          "count" : 1
        }
      ]
    }
  }
}</pre>
</div>
<div class="calloutlist">
<table border="0" summary="Callout list">
<tr>
<td align="left" valign="top" width="5%">
<p><a href="#CO592-1"><i class="conum" data-value="1"></i></a></p>
</td>
<td align="left" valign="top">
<p>This time the <code class="literal">format</code> has been identified as <code class="literal">semi_structured_text</code>.</p>
</td>
</tr>
<tr>
<td align="left" valign="top" width="5%">
<p><a href="#CO592-2"><i class="conum" data-value="2"></i></a></p>
</td>
<td align="left" valign="top">
<p>The <code class="literal">multiline_start_pattern</code> is set on the basis that the timestamp appears
in the first line of each multi-line log message.</p>
</td>
</tr>
<tr>
<td align="left" valign="top" width="5%">
<p><a href="#CO592-3"><i class="conum" data-value="3"></i></a></p>
</td>
<td align="left" valign="top">
<p>A very simple <code class="literal">grok_pattern</code> has been created, which extracts the timestamp
and recognizable fields that appear in every analyzed message. In this case
the only field that was recognized beyond the timestamp was the log level.</p>
</td>
</tr>
</table>
</div>
</div>

<div class="section">
<div class="titlepage"><div><div>
<h4 class="title">
<a id="ml-find-file-structure-example-grok"></a>Specifying <code class="literal">grok_pattern</code> as query parameter<a class="edit_me edit_me_private" rel="nofollow" title="Editing on GitHub is available to Elastic" href="https://github.com/elastic/elasticsearch/edit/7.7/docs/reference/ml/anomaly-detection/apis/find-file-structure.asciidoc">edit</a>
</h4>
</div></div></div>
<p>If you recognize more fields than the simple <code class="literal">grok_pattern</code> produced by the
structure finder unaided then you can resubmit the request specifying a more
advanced <code class="literal">grok_pattern</code> as a query parameter and the structure finder will
calculate <code class="literal">field_stats</code> for your additional fields.</p>
<p>In the case of the Elasticsearch log a more complete Grok pattern is
<code class="literal">\[%{TIMESTAMP_ISO8601:timestamp}\]\[%{LOGLEVEL:loglevel} *\]\[%{JAVACLASS:class} *\] \[%{HOSTNAME:node}\] %{JAVALOGMESSAGE:message}</code>.
You can analyze the same log file again, submitting this <code class="literal">grok_pattern</code> as a
query parameter (appropriately URL escaped):</p>
<div class="pre_wrapper lang-js">
<pre class="programlisting prettyprint lang-js">curl -s -H "Content-Type: application/json" -XPOST "localhost:9200/_ml/find_file_structure?pretty&amp;format=semi_structured_text&amp;grok_pattern=%5C%5B%25%7BTIMESTAMP_ISO8601:timestamp%7D%5C%5D%5C%5B%25%7BLOGLEVEL:loglevel%7D%20*%5C%5D%5C%5B%25%7BJAVACLASS:class%7D%20*%5C%5D%20%5C%5B%25%7BHOSTNAME:node%7D%5C%5D%20%25%7BJAVALOGMESSAGE:message%7D" -T "$ES_HOME/logs/elasticsearch.log"</pre>
</div>
<p>If the request does not encounter errors, the result will look something like
this:</p>
<div class="pre_wrapper lang-js">
<pre class="programlisting prettyprint lang-js">{
  "num_lines_analyzed" : 53,
  "num_messages_analyzed" : 53,
  "sample_start" : "[2018-09-27T14:39:28,518][INFO ][o.e.e.NodeEnvironment    ] [node-0] using [1] data paths, mounts [[/ (/dev/disk1)]], net usable_space [165.4gb], net total_space [464.7gb], types [hfs]\n[2018-09-27T14:39:28,521][INFO ][o.e.e.NodeEnvironment    ] [node-0] heap size [494.9mb], compressed ordinary object pointers [true]\n",
  "charset" : "UTF-8",
  "has_byte_order_marker" : false,
  "format" : "semi_structured_text",
  "multiline_start_pattern" : "^\\[\\b\\d{4}-\\d{2}-\\d{2}[T ]\\d{2}:\\d{2}",
  "grok_pattern" : "\\[%{TIMESTAMP_ISO8601:timestamp}\\]\\[%{LOGLEVEL:loglevel} *\\]\\[%{JAVACLASS:class} *\\] \\[%{HOSTNAME:node}\\] %{JAVALOGMESSAGE:message}", <a id="CO593-1"></a><i class="conum" data-value="1"></i>
  "timestamp_field" : "timestamp",
  "joda_timestamp_formats" : [
    "ISO8601"
  ],
  "java_timestamp_formats" : [
    "ISO8601"
  ],
  "need_client_timezone" : true,
  "mappings" : {
    "@timestamp" : {
      "type" : "date"
    },
    "class" : {
      "type" : "keyword"
    },
    "loglevel" : {
      "type" : "keyword"
    },
    "message" : {
      "type" : "text"
    },
    "node" : {
      "type" : "keyword"
    }
  },
  "ingest_pipeline" : {
    "description" : "Ingest pipeline created by file structure finder",
    "processors" : [
      {
        "grok" : {
          "field" : "message",
          "patterns" : [
            "\\[%{TIMESTAMP_ISO8601:timestamp}\\]\\[%{LOGLEVEL:loglevel} *\\]\\[%{JAVACLASS:class} *\\] \\[%{HOSTNAME:node}\\] %{JAVALOGMESSAGE:message}"
          ]
        }
      },
      {
        "date" : {
          "field" : "timestamp",
          "timezone" : "{{ event.timezone }}",
          "formats" : [
            "ISO8601"
          ]
        }
      },
      {
        "remove" : {
          "field" : "timestamp"
        }
      }
    ]
  },
  "field_stats" : { <a id="CO593-2"></a><i class="conum" data-value="2"></i>
    "class" : {
      "count" : 53,
      "cardinality" : 14,
      "top_hits" : [
        {
          "value" : "o.e.p.PluginsService",
          "count" : 26
        },
        {
          "value" : "o.e.c.m.MetaDataIndexTemplateService",
          "count" : 8
        },
        {
          "value" : "o.e.n.Node",
          "count" : 7
        },
        {
          "value" : "o.e.e.NodeEnvironment",
          "count" : 2
        },
        {
          "value" : "o.e.a.ActionModule",
          "count" : 1
        },
        {
          "value" : "o.e.c.s.ClusterApplierService",
          "count" : 1
        },
        {
          "value" : "o.e.c.s.MasterService",
          "count" : 1
        },
        {
          "value" : "o.e.d.DiscoveryModule",
          "count" : 1
        },
        {
          "value" : "o.e.g.GatewayService",
          "count" : 1
        },
        {
          "value" : "o.e.l.LicenseService",
          "count" : 1
        }
      ]
    },
    "loglevel" : {
      "count" : 53,
      "cardinality" : 3,
      "top_hits" : [
        {
          "value" : "INFO",
          "count" : 51
        },
        {
          "value" : "DEBUG",
          "count" : 1
        },
        {
          "value" : "WARN",
          "count" : 1
        }
      ]
    },
    "message" : {
      "count" : 53,
      "cardinality" : 53,
      "top_hits" : [
        {
          "value" : "Using REST wrapper from plugin org.elasticsearch.xpack.security.Security",
          "count" : 1
        },
        {
          "value" : "adding template [.monitoring-alerts] for index patterns [.monitoring-alerts-6]",
          "count" : 1
        },
        {
          "value" : "adding template [.monitoring-beats] for index patterns [.monitoring-beats-6-*]",
          "count" : 1
        },
        {
          "value" : "adding template [.monitoring-es] for index patterns [.monitoring-es-6-*]",
          "count" : 1
        },
        {
          "value" : "adding template [.monitoring-kibana] for index patterns [.monitoring-kibana-6-*]",
          "count" : 1
        },
        {
          "value" : "adding template [.monitoring-logstash] for index patterns [.monitoring-logstash-6-*]",
          "count" : 1
        },
        {
          "value" : "adding template [.triggered_watches] for index patterns [.triggered_watches*]",
          "count" : 1
        },
        {
          "value" : "adding template [.watch-history-9] for index patterns [.watcher-history-9*]",
          "count" : 1
        },
        {
          "value" : "adding template [.watches] for index patterns [.watches*]",
          "count" : 1
        },
        {
          "value" : "starting ...",
          "count" : 1
        }
      ]
    },
    "node" : {
      "count" : 53,
      "cardinality" : 1,
      "top_hits" : [
        {
          "value" : "node-0",
          "count" : 53
        }
      ]
    },
    "timestamp" : {
      "count" : 53,
      "cardinality" : 28,
      "earliest" : "2018-09-27T14:39:28,518",
      "latest" : "2018-09-27T14:39:37,012",
      "top_hits" : [
        {
          "value" : "2018-09-27T14:39:29,859",
          "count" : 10
        },
        {
          "value" : "2018-09-27T14:39:29,860",
          "count" : 9
        },
        {
          "value" : "2018-09-27T14:39:29,858",
          "count" : 6
        },
        {
          "value" : "2018-09-27T14:39:28,523",
          "count" : 3
        },
        {
          "value" : "2018-09-27T14:39:34,234",
          "count" : 2
        },
        {
          "value" : "2018-09-27T14:39:28,518",
          "count" : 1
        },
        {
          "value" : "2018-09-27T14:39:28,521",
          "count" : 1
        },
        {
          "value" : "2018-09-27T14:39:28,522",
          "count" : 1
        },
        {
          "value" : "2018-09-27T14:39:29,861",
          "count" : 1
        },
        {
          "value" : "2018-09-27T14:39:32,786",
          "count" : 1
        }
      ]
    }
  }
}</pre>
</div>
<div class="calloutlist">
<table border="0" summary="Callout list">
<tr>
<td align="left" valign="top" width="5%">
<p><a href="#CO593-1"><i class="conum" data-value="1"></i></a></p>
</td>
<td align="left" valign="top">
<p>The <code class="literal">grok_pattern</code> in the output is now the overridden one supplied in the
query parameter.</p>
</td>
</tr>
<tr>
<td align="left" valign="top" width="5%">
<p><a href="#CO593-2"><i class="conum" data-value="2"></i></a></p>
</td>
<td align="left" valign="top">
<p>The returned <code class="literal">field_stats</code> include entries for the fields from the
overridden <code class="literal">grok_pattern</code>.</p>
</td>
</tr>
</table>
</div>
<p>The URL escaping is hard, so if you are working interactively it is best to use
the machine learning UI!</p>
</div>

</div>

</div>
<div class="navfooter">
<span class="prev">
<a href="ml-estimate-model-memory.html">« Estimate anomaly detection jobs model memory API</a>
</span>
<span class="next">
<a href="ml-flush-job.html">Flush jobs API »</a>
</span>
</div>
</div>

                  <!-- end body -->
                </div>
                <div class="col-xs-12 col-sm-4 col-md-4" id="right_col">
                  <div id="rtpcontainer" style="display: block;">
                    <div class="mktg-promo">
                      <h3>Most Popular</h3>
                      <ul class="icons">
                        <li class="icon-elasticsearch-white"><a href="https://www.elastic.co/webinars/getting-started-elasticsearch?baymax=default&amp;elektra=docs&amp;storm=top-video">Get Started with Elasticsearch: Video</a></li>
                        <li class="icon-kibana-white"><a href="https://www.elastic.co/webinars/getting-started-kibana?baymax=default&amp;elektra=docs&amp;storm=top-video">Intro to Kibana: Video</a></li>
                        <li class="icon-logstash-white"><a href="https://www.elastic.co/webinars/introduction-elk-stack?baymax=default&amp;elektra=docs&amp;storm=top-video">ELK for Logs &amp; Metrics: Video</a></li>
                      </ul>
                    </div>
                  </div>
                </div>
              </div>
            </div>
          </section>

        </div>


<div id="elastic-footer"></div>
<script src="https://www.elastic.co/elastic-footer.js"></script>
<!-- Footer Section end-->

      </section>
    </div>

<script src="/guide/static/jquery.js"></script>
<script type="text/javascript" src="/guide/static/docs.js"></script>
<script type="text/javascript">
  window.initial_state = {}</script>
  </body>
</html>
